Introduction

This R notebook enables the reproduction of the analysis described in:

Tracing production instability in a clonally-derived CHO cell line using single cell transcriptomics

In this study, the four biological replicates of a clonally derived CHO cell line were sampled at 72hrs post-seeding and analysed on the BD Rhapsody system whole transcriptome analysis. The FASTQ data were converted to a cell gene count matrix using the Seven Bridges Genomics BD Rhapsody WTA pipeline and combined into a single sample.

Raw Data Availibility

SRA ID: PRJNA661407

Preparation

Load packages

library(monocle)
library(plyr)
library(dplyr)
library(ggExtra)
library(reshape)
library(colorRamps)
library(stringr)
library(Seurat)
library(BiocParallel)
library(ggpubr)
library(DT)
library(WebGestaltR)
library(ggalt)
library(biomaRt)
library(patchwork)
library(viridis)
library(gridExtra)
library(grid)
library(gganimate)
library(hrbrthemes)
library(jcolors)
library(cowplot)
library(data.table)
library(GGally)
library(ggplotify)
library(stringr)
library(writexl)

Set seed

Plotting utilites

Calculate relative expression

Create a function to determine the relative expression of a gene from a Monocle cell dataset. When the expression of a gene is than the detection limit, the gene is equal to the detection limit.

Import raw data

scRNASeq

We import data from the Seven Bridges Genomics (SBG) platform for analysis in R. The UMI data for each replicate is stored in a separate CSV file with each row representing an individual cell, the column represents a gene. In this experiment, 4 biological replicates for the CHOK1 DP12 cell line were analysed using Rhapsody WTA. We create a batch ID than be used to regress any technical variation due to batch. We determine the genes detected in at least one replicate. If a gene is not detected in a replicate we assign a 0 UMI value for that replicate. The replicates are then combined in a single matrix.

SBG output

Create Monocle object

The primary analysis package for this analysis Monocle v2. To use this package we must first create a cell dataset (CDS) object containing the raw Rhapsody data. During this process we assign a detection limit along with the expressionFamily - in this case negbinomial as appropriate for UMI data.

[1] "Raw data for 4673 and 20594  genes captured"

bulk RNASeq

To compare a matched bulkRNASeq dataset to our single cell data were calculated a gene-level transcripts per million (TPM) value using Kallisto.

Replicate comparison

scRNASeq

To compare to the bulk RNASeq data we merge the scRNASeq to pseudoBulk profiles, 1 for each replicate and convert expression to TPM. We then determine the agreement between the replicates

bulk RNASeq

Determine the agreement between the bulkRNASeq replicates # scRNASeq v bulkRNASeq Comparison of each scRNASeq sample to it’s respective matched bulkRNASeq sample.

Map gene IDs

Correlation between single cell and bulk RNASeq data

scRNASeq data preprocessing

The first stage of preprocessing in the Monocle workflow aims to eliminate poor quality cells from further analysis. In this section we calculate metrics to enable filtering of poor quality cells from the analysis - total UMIs, and fraction of UMIs that originate from mitochondrial genes.

Filter by Total UMIs

Cells that have too few UMIs per cells as well as those that have too many UMIs per cell are removed from the analysis
Figure

Figure

Filter by mtDNA reads

A cell with >= 15% of the total UMIs originating from mitochondrial genes is removed
Figure

Figure

Remove poor quality cells

Figure

Figure

Filter Genes by expression

We now remove genes that are not expressed in more than 50 cells in our dataset or the maximum expression is less than 2 UMIs in any cell
Figure

Figure

Figure 1

Gene annotation

The SBG platform utilises the ENSEMBL GTF file for the PICR genome. To improve the annotation of the genes we utlise the corresponding Entrez IDs for those genes labelled with and “ENSCGRG” IDs to obtain a gene symbol

Cell cycle scoring

For the next section we used the cell cycle scoring function of Seurat to determine which phase of the cell cycles cells were in. Using this function will allow us to correct the effect of cell cycle in subsequent analyses.

Create a Seurat object

Preprocess Seurat

Before scoring cells by the cell cycle phase any variation due to batch is removed

Specify cell cycle genes

Here we use custom CHO cell genes involved in cell cycle

Calculate the cell cycle scores

Add cell cycle scores to CDS

tSNE Analysis

Identify variable genes

Figure

Figure

Select PCs

Figure

Figure

t-Stocastic neighbour embedding

Identify tSNE clusters

Distance cutoff calculated to 3.224882 

## Effect of CC correction

tSNE density

tSNE clusters

To identify groups of cells form the tSNE plot we use the louvain method in monocle with K=100. Each cluster is assinged a color for reference.
Figure

Figure

Figure 2

Differential expression

Using Monocle’s differential gene test the genes that differ between the clusters of cells are identified. We again regress out confounding factors i.e. batch and cell cycle phase

462.535 sec elapsed

Anti-IL8 mAb gene expression

bulk RNASeq

## scRNASeq

HC & LC violin

HC tSNE

HC cluster expression

[1] "Heavy chain DE q-value for cluster =  1.6e-53"

LC tSNE

## HC cluster expression

[1] "Light chain DE q-values for cluster =  1.3e-36"

Figure 3

Trajectory analysis

Construct trajectory

using the genes found to vary beteen the identified clusters we first project onto a 2D space using the DDRTree algorithm before ording the cells in pseduotime
Figure

Figure

Figure

Figure

Median relative HC & LC in each cell state

Differential expression of LC & HC

HC state expression

HC trajectory

LC state expression

LC trajectory

Figure 5

Create and save figure 5 in the manuscript.

Expression of CHO genes along trajectory

Set the root of the Monocle trajectory

Cell state 1 is set as the root or beginning of the trajectory ## Pseudotime differential expression Identification of genes that correlated with Pseudotime. Those genes found to have a qval < 0.01 using the Monocle differentialGeneTest function were considered significant

[1] TRUE

Cluster analysis

Enrichment analysis

Use WebGestaltR to determine if the identified clusters of genes are enriched when compared to GO. Those biological processes with a Benjamini Hochberg adjusted p-value < 0.05 were considered significantly enriched.

Enriched GO BPs

Cluster 1

### Cluster 2

CHO cell gene expression

Overlay the expression of genes found to significantly correlate with the progression of cells along the trajectory.

Psap

Plot the expression of the Prosaposin gene ### Hmox1 Plot the expression of the Heme oxygenase 1 gene ### Fth1 Plot the expression of the Ferritin 1 heavy chain 1 gene

Figure 6

Create and save figure 6 in the manuscript.

Session info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.0.2 (2020-06-22)
 os       Ubuntu 16.04.5 LTS          
 system   x86_64, linux-gnu           
 ui       X11                         
 language (EN)                        
 collate  en_IE.UTF-8                 
 ctype    en_IE.UTF-8                 
 tz       Europe/Dublin               
 date     2020-10-05                  

─ Packages ───────────────────────────────────────────────────────────────────
 ! package        * version  date       lib source        
   abind            1.4-5    2016-07-21 [1] CRAN (R 4.0.2)
   AnnotationDbi    1.50.1   2020-06-29 [1] Bioconductor  
   apcluster        1.4.8    2019-08-21 [1] CRAN (R 4.0.2)
   ape              5.4      2020-06-03 [1] CRAN (R 4.0.2)
   ash              1.0-15   2015-09-01 [1] CRAN (R 4.0.2)
   askpass          1.1      2019-01-13 [1] CRAN (R 4.0.2)
   assertthat       0.2.1    2019-03-21 [1] CRAN (R 4.0.2)
   backports        1.1.8    2020-06-17 [1] CRAN (R 4.0.2)
   Biobase        * 2.48.0   2020-04-27 [1] Bioconductor  
   BiocFileCache    1.12.0   2020-04-27 [1] Bioconductor  
   BiocGenerics   * 0.34.0   2020-04-27 [1] Bioconductor  
   BiocManager      1.30.10  2019-11-16 [1] CRAN (R 4.0.2)
   BiocParallel   * 1.22.0   2020-04-27 [1] Bioconductor  
   biomaRt        * 2.44.1   2020-06-17 [1] Bioconductor  
   bit              1.1-15.2 2020-02-10 [1] CRAN (R 4.0.2)
   bit64            0.9-7    2017-05-08 [1] CRAN (R 4.0.2)
   blob             1.2.1    2020-01-20 [1] CRAN (R 4.0.2)
   bookdown         0.20     2020-06-23 [1] CRAN (R 4.0.2)
   broom            0.7.0    2020-07-09 [1] CRAN (R 4.0.2)
   callr            3.4.3    2020-03-28 [1] CRAN (R 4.0.2)
   car              3.0-8    2020-05-21 [1] CRAN (R 4.0.2)
   carData          3.0-4    2020-05-22 [1] CRAN (R 4.0.2)
   cellranger       1.1.0    2016-07-27 [1] CRAN (R 4.0.2)
   cli              2.0.2    2020-02-28 [1] CRAN (R 4.0.2)
 P cluster          2.1.0    2019-06-19 [?] CRAN (R 4.0.0)
 P codetools        0.2-16   2018-12-24 [?] CRAN (R 4.0.0)
   colorRamps     * 2.3      2012-10-29 [1] CRAN (R 4.0.2)
   colorspace       1.4-1    2019-03-18 [1] CRAN (R 4.0.2)
   combinat         0.0-8    2012-10-29 [1] CRAN (R 4.0.2)
   cowplot        * 1.0.0    2019-07-11 [1] CRAN (R 4.0.2)
   cpp11            0.2.1    2020-08-11 [1] CRAN (R 4.0.2)
   crayon           1.3.4    2017-09-16 [1] CRAN (R 4.0.2)
   crosstalk        1.1.0.1  2020-03-13 [1] CRAN (R 4.0.2)
   curl             4.3      2019-12-02 [1] CRAN (R 4.0.2)
   data.table     * 1.12.8   2019-12-09 [1] CRAN (R 4.0.2)
   DBI              1.1.0    2019-12-15 [1] CRAN (R 4.0.2)
   dbplyr           1.4.4    2020-05-27 [1] CRAN (R 4.0.2)
   DDRTree        * 0.1.5    2017-04-30 [1] CRAN (R 4.0.2)
   densityClust     0.3      2017-10-24 [1] CRAN (R 4.0.2)
   desc             1.2.0    2018-05-01 [1] CRAN (R 4.0.2)
   devtools         2.3.0    2020-04-10 [1] CRAN (R 4.0.2)
   digest           0.6.25   2020-02-23 [1] CRAN (R 4.0.2)
   docopt           0.7.1    2020-06-24 [1] CRAN (R 4.0.2)
   doParallel       1.0.15   2019-08-02 [1] CRAN (R 4.0.2)
   doRNG            1.8.2    2020-01-27 [1] CRAN (R 4.0.2)
   dplyr          * 1.0.0    2020-05-29 [1] CRAN (R 4.0.2)
   DT             * 0.14     2020-06-24 [1] CRAN (R 4.0.2)
   ellipsis         0.3.1    2020-05-15 [1] CRAN (R 4.0.2)
   evaluate         0.14     2019-05-28 [1] CRAN (R 4.0.2)
   extrafont        0.17     2014-12-08 [1] CRAN (R 4.0.2)
   extrafontdb      1.0      2012-06-11 [1] CRAN (R 4.0.2)
   fansi            0.4.1    2020-01-08 [1] CRAN (R 4.0.2)
   farver           2.0.3    2020-01-16 [1] CRAN (R 4.0.2)
   fastICA          1.2-2    2019-07-08 [1] CRAN (R 4.0.2)
   fastmap          1.0.1    2019-10-08 [1] CRAN (R 4.0.2)
   fitdistrplus     1.1-1    2020-05-19 [1] CRAN (R 4.0.2)
   FNN              1.1.3    2019-02-15 [1] CRAN (R 4.0.2)
   forcats          0.5.0    2020-03-01 [1] CRAN (R 4.0.2)
   foreach          1.5.0    2020-03-30 [1] CRAN (R 4.0.2)
 P foreign          0.8-80   2020-05-24 [?] CRAN (R 4.0.2)
   formatR          1.7      2019-06-11 [1] CRAN (R 4.0.2)
   fs               1.4.2    2020-06-30 [1] CRAN (R 4.0.2)
   future           1.18.0   2020-07-09 [1] CRAN (R 4.0.2)
   future.apply     1.6.0    2020-07-01 [1] CRAN (R 4.0.2)
   gdtools          0.2.2    2020-04-03 [1] CRAN (R 4.0.2)
   generics         0.0.2    2018-11-29 [1] CRAN (R 4.0.2)
   GGally         * 2.0.0    2020-06-06 [1] CRAN (R 4.0.2)
   ggalt          * 0.4.0    2017-02-15 [1] CRAN (R 4.0.2)
   gganimate      * 1.0.6    2020-07-08 [1] CRAN (R 4.0.2)
   ggExtra        * 0.9      2019-08-27 [1] CRAN (R 4.0.2)
   ggplot2        * 3.3.2    2020-06-19 [1] CRAN (R 4.0.2)
   ggplotify      * 0.0.5    2020-03-12 [1] CRAN (R 4.0.2)
   ggpubr         * 0.4.0    2020-06-27 [1] CRAN (R 4.0.2)
   ggrepel          0.8.2    2020-03-08 [1] CRAN (R 4.0.2)
   ggridges         0.5.2    2020-01-12 [1] CRAN (R 4.0.2)
   ggsignif         0.6.0    2019-08-08 [1] CRAN (R 4.0.2)
   globals          0.12.5   2019-12-07 [1] CRAN (R 4.0.2)
   glue             1.4.1    2020-05-13 [1] CRAN (R 4.0.2)
   gridExtra      * 2.3      2017-09-09 [1] CRAN (R 4.0.2)
   gridGraphics     0.5-0    2020-02-25 [1] CRAN (R 4.0.2)
   gtable           0.3.0    2019-03-25 [1] CRAN (R 4.0.2)
   haven            2.3.1    2020-06-01 [1] CRAN (R 4.0.2)
   highr            0.8      2019-03-20 [1] CRAN (R 4.0.2)
   hms              0.5.3    2020-01-08 [1] CRAN (R 4.0.2)
   hrbrthemes     * 0.8.0    2020-03-06 [1] CRAN (R 4.0.2)
   HSMMSingleCell   1.8.0    2020-05-07 [1] Bioconductor  
   htmltools        0.5.0    2020-06-16 [1] CRAN (R 4.0.2)
   htmlwidgets      1.5.1    2019-10-08 [1] CRAN (R 4.0.2)
   httpuv           1.5.4    2020-06-06 [1] CRAN (R 4.0.2)
   httr             1.4.1    2019-08-05 [1] CRAN (R 4.0.2)
   ica              1.0-2    2018-05-24 [1] CRAN (R 4.0.2)
   igraph           1.2.5    2020-03-19 [1] CRAN (R 4.0.2)
   IRanges          2.22.2   2020-05-21 [1] Bioconductor  
   irlba          * 2.3.3    2019-02-05 [1] CRAN (R 4.0.2)
   iterators        1.0.12   2019-07-26 [1] CRAN (R 4.0.2)
   jcolors        * 0.0.4    2019-05-22 [1] CRAN (R 4.0.2)
   jsonlite         1.7.0    2020-06-25 [1] CRAN (R 4.0.2)
 P KernSmooth       2.23-17  2020-04-26 [?] CRAN (R 4.0.0)
   knitr          * 1.29     2020-06-23 [1] CRAN (R 4.0.2)
   labeling         0.3      2014-08-23 [1] CRAN (R 4.0.2)
   later            1.1.0.1  2020-06-05 [1] CRAN (R 4.0.2)
 P lattice          0.20-41  2020-04-02 [?] CRAN (R 4.0.0)
   lazyeval         0.2.2    2019-03-15 [1] CRAN (R 4.0.2)
   leiden           0.3.3    2020-02-04 [1] CRAN (R 4.0.2)
   lifecycle        0.2.0    2020-03-06 [1] CRAN (R 4.0.2)
   limma            3.44.3   2020-06-12 [1] Bioconductor  
   listenv          0.8.0    2019-12-05 [1] CRAN (R 4.0.2)
   lmtest           0.9-37   2019-04-30 [1] CRAN (R 4.0.2)
   magick           2.4.0    2020-06-23 [1] CRAN (R 4.0.2)
   magrittr         1.5      2014-11-22 [1] CRAN (R 4.0.2)
   maps             3.3.0    2018-04-03 [1] CRAN (R 4.0.2)
 P MASS             7.3-51.6 2020-04-26 [?] CRAN (R 4.0.0)
 P Matrix         * 1.2-18   2019-11-27 [?] CRAN (R 4.0.0)
   matrixStats      0.56.0   2020-03-13 [1] CRAN (R 4.0.2)
   memoise          1.1.0    2017-04-21 [1] CRAN (R 4.0.2)
   mime             0.9      2020-02-04 [1] CRAN (R 4.0.2)
   miniUI           0.1.1.1  2018-05-18 [1] CRAN (R 4.0.2)
   monocle        * 2.16.0   2020-04-27 [1] Bioconductor  
   munsell          0.5.0    2018-06-12 [1] CRAN (R 4.0.2)
 P nlme             3.1-148  2020-05-24 [?] CRAN (R 4.0.2)
   openssl          1.4.2    2020-06-27 [1] CRAN (R 4.0.2)
   openxlsx         4.1.5    2020-05-06 [1] CRAN (R 4.0.2)
   packrat          0.5.0    2018-11-14 [1] CRAN (R 4.0.2)
   patchwork      * 1.0.1    2020-06-22 [1] CRAN (R 4.0.2)
   pbapply          1.4-2    2019-08-31 [1] CRAN (R 4.0.2)
   pheatmap         1.0.12   2019-01-04 [1] CRAN (R 4.0.2)
   pillar           1.4.6    2020-07-10 [1] CRAN (R 4.0.2)
   pkgbuild         1.0.8    2020-05-07 [1] CRAN (R 4.0.2)
   pkgconfig        2.0.3    2019-09-22 [1] CRAN (R 4.0.2)
   pkgload          1.1.0    2020-05-29 [1] CRAN (R 4.0.2)
   plotly           4.9.2.1  2020-04-04 [1] CRAN (R 4.0.2)
   plyr           * 1.8.6    2020-03-03 [1] CRAN (R 4.0.2)
   png              0.1-7    2013-12-03 [1] CRAN (R 4.0.2)
   prettyunits      1.1.1    2020-01-24 [1] CRAN (R 4.0.2)
   processx         3.4.3    2020-07-05 [1] CRAN (R 4.0.2)
   progress         1.2.2    2019-05-16 [1] CRAN (R 4.0.2)
   proj4            1.0-10   2020-03-02 [1] CRAN (R 4.0.2)
   promises         1.1.1    2020-06-09 [1] CRAN (R 4.0.2)
   proxy            0.4-24   2020-04-25 [1] CRAN (R 4.0.2)
   ps               1.3.3    2020-05-08 [1] CRAN (R 4.0.2)
   purrr            0.3.4    2020-04-17 [1] CRAN (R 4.0.2)
   qlcMatrix        0.9.7    2018-04-20 [1] CRAN (R 4.0.2)
   R6               2.4.1    2019-11-12 [1] CRAN (R 4.0.2)
   RANN             2.6.1    2019-01-08 [1] CRAN (R 4.0.2)
   rappdirs         0.3.1    2016-03-28 [1] CRAN (R 4.0.2)
   RColorBrewer     1.1-2    2014-12-07 [1] CRAN (R 4.0.2)
   Rcpp             1.0.5    2020-07-06 [1] CRAN (R 4.0.2)
   RcppAnnoy        0.0.16   2020-03-08 [1] CRAN (R 4.0.2)
   readr            1.3.1    2018-12-21 [1] CRAN (R 4.0.2)
   readxl           1.3.1    2019-03-13 [1] CRAN (R 4.0.2)
   remotes          2.1.1    2020-02-15 [1] CRAN (R 4.0.2)
   reshape        * 0.8.8    2018-10-23 [1] CRAN (R 4.0.2)
   reshape2         1.4.4    2020-04-09 [1] CRAN (R 4.0.2)
   reticulate       1.16     2020-05-27 [1] CRAN (R 4.0.2)
   rio              0.5.16   2018-11-26 [1] CRAN (R 4.0.2)
   rlang            0.4.7    2020-07-09 [1] CRAN (R 4.0.2)
   rmarkdown        2.3      2020-06-18 [1] CRAN (R 4.0.2)
   rmdformats     * 0.3.7    2020-03-11 [1] CRAN (R 4.0.2)
   rngtools         1.5      2020-01-23 [1] CRAN (R 4.0.2)
   ROCR             1.0-11   2020-05-02 [1] CRAN (R 4.0.2)
   rprojroot        1.3-2    2018-01-03 [1] CRAN (R 4.0.2)
   RSQLite          2.2.0    2020-01-07 [1] CRAN (R 4.0.2)
   rstatix          0.6.0    2020-06-18 [1] CRAN (R 4.0.2)
   rstudioapi       0.11     2020-02-07 [1] CRAN (R 4.0.2)
   rsvd             1.0.3    2020-02-17 [1] CRAN (R 4.0.2)
   Rtsne            0.15     2018-11-10 [1] CRAN (R 4.0.2)
   Rttf2pt1         1.3.8    2020-01-10 [1] CRAN (R 4.0.2)
   rvcheck          0.1.8    2020-03-01 [1] CRAN (R 4.0.2)
   S4Vectors        0.26.1   2020-05-16 [1] Bioconductor  
   scales           1.1.1    2020-05-11 [1] CRAN (R 4.0.2)
   sctransform      0.2.1    2019-12-17 [1] CRAN (R 4.0.2)
   sessioninfo      1.1.1    2018-11-05 [1] CRAN (R 4.0.2)
   Seurat         * 3.1.5    2020-04-16 [1] CRAN (R 4.0.2)
   shiny            1.5.0    2020-06-23 [1] CRAN (R 4.0.2)
   slam             0.1-47   2019-12-21 [1] CRAN (R 4.0.2)
   sparsesvd        0.2      2019-07-15 [1] CRAN (R 4.0.2)
   stringi          1.4.6    2020-02-17 [1] CRAN (R 4.0.2)
   stringr        * 1.4.0    2019-02-10 [1] CRAN (R 4.0.2)
 P survival         3.2-3    2020-06-13 [?] CRAN (R 4.0.1)
   svglite          1.2.3.2  2020-07-07 [1] CRAN (R 4.0.2)
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   testthat         2.3.2    2020-03-02 [1] CRAN (R 4.0.2)
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   tictoc           1.0      2014-06-17 [1] CRAN (R 4.0.2)
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   tidyselect       1.1.0    2020-05-11 [1] CRAN (R 4.0.2)
   tsne             0.1-3    2016-07-15 [1] CRAN (R 4.0.2)
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   usethis          1.6.1    2020-04-29 [1] CRAN (R 4.0.2)
   uwot             0.1.8    2020-03-16 [1] CRAN (R 4.0.2)
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   VGAM           * 1.1-3    2020-04-28 [1] CRAN (R 4.0.2)
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   writexl        * 1.3      2020-05-05 [1] CRAN (R 4.0.2)
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[1] /mnt/HDD2/colin/CHO_cell_scRNASeq/packrat/lib/x86_64-pc-linux-gnu/4.0.2
[2] /mnt/HDD2/colin/CHO_cell_scRNASeq/packrat/lib-ext/x86_64-pc-linux-gnu/4.0.2
[3] /mnt/HDD2/colin/CHO_cell_scRNASeq/packrat/lib-R/x86_64-pc-linux-gnu/4.0.2

 P ── Loaded and on-disk path mismatch.